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Mastering Geospatial Analysis with Python

You're reading from   Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
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Authors (3):
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Silas Toms Silas Toms
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Silas Toms
Paul Crickard Paul Crickard
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Paul Crickard
Eric van Rees Eric van Rees
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Eric van Rees
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Toc

Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management 2. Introduction to Geospatial Code Libraries FREE CHAPTER 3. Introduction to Geospatial Databases 4. Data Types, Storage, and Conversion 5. Vector Data Analysis 6. Raster Data Processing 7. Geoprocessing with Geodatabases 8. Automating QGIS Analysis 9. ArcGIS API for Python and ArcGIS Online 10. Geoprocessing with a GPU Database 11. Flask and GeoAlchemy2 12. GeoDjango 13. Geospatial REST API 14. Cloud Geodatabase Analysis and Visualization 15. Automating Cloud Cartography 16. Python Geoprocessing with Hadoop 17. Other Books You May Enjoy

Automating QGIS Analysis

This book has introduced you to using Python from the command line, in a Jupyter Notebook, and in an IDE to perform geospatial tasks. While these three tools will allow you to accomplish your tasks, there are many times when work needs to be done using desktop GIS software.

QGIS, a popular open source GIS application, provides desktop GIS functionality with the ability to work in a Python console and the ability to write toolboxes and plugins using Python. In this chapter, you will learn how to manipulate desktop GIS data using Python and how to automate these tasks using toolboxes and plugins.

In this chapter, you will learn how to:

  • Load and save layers
  • Create layers from API data sources
  • Add, edit, and delete features
  • Select specific features
  • Call geoprocessing functions
  • Write geoprocessing toolboxes
  • Write plugins
...
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